I am aware that truncated distributions are not yet supported in brms formulas for mixture models, but was wondering if there was a strategy for getting around this limitation.
mix <- mixture(gaussian, gaussian) prior <- c( prior(normal(mup1, varp1), Intercept, dpar = mu1), prior(normal(mup2, varp2), Intercept, dpar = mu2) ) fit1 <- brm(bf(response ~ 1, theta1 ~ s(days, k=15)), data = ts, family = mix, prior = prior, chains = 2, stanvars = stanvars)
However, the distribution of my response variable looks like this, because the instrument that measures these values has a saturation limit:
I suspect this can be done by making
mix a mixture of custom distributions, but I’m not sure how to go about it.
- Operating System: Debian 9
- brms Version: 2.3.1